• 关键词：水质  超阈值风险  成丛随机点过程复合模型

• 基金项目：国家自然科学基金(59509005)

• 陈小红
• 中山大学水资源与环境研究所, 广州 510275

• 涂新军
• 中山大学水资源与环境研究所, 广州 510275

• 摘要：将水质当作随机变量,基于随机点过程理论,构造了水质超阈值风险分析的成丛随机点过程复合(CSPPC)模型,并应用于深圳市深圳河河口段水体DO、COD浓度超阈值的风险率估算,由实际资料对该河段水体DO、COD浓度超阈值点过程的分布进行了拟合优度试验,获得满意计算结果.

• Abstract：Taking water quality as a stochastic variable, the Clustering Stochastic Point Process Compound (CSPPC) model for the risk rate of concentrations exceeding the threshold was developed based on the theory of stochastic point process.The model was used at the downstream reach of Shenzhen River in Shenzhen City to evaluate the risk rates of DO and COD exceeding the given thresholds respectively.The distributions of the point process for DO and COD exceeding the thresholds were tested and fitted respectively by measured data.The results are satisfactory.

• Key words：water quality  risk rate  threshold  clustering stochastic point process compound model

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